Survey of Deformable Convolutional Networks.
LIU Weiguang, LIU Dong, W Lu - Journal of Frontiers of …, 2023 - search.ebscohost.com
In recent years, with the rapid development of deep learning, deformable convolutional
networks have received extensive attention because of their powerful feature extraction …
networks have received extensive attention because of their powerful feature extraction …
Fully cross-attention transformer for guided depth super-resolution
I Ariav, I Cohen - Sensors, 2023 - mdpi.com
Modern depth sensors are often characterized by low spatial resolution, which hinders their
use in real-world applications. However, the depth map in many scenarios is accompanied …
use in real-world applications. However, the depth map in many scenarios is accompanied …
Depth Map Super-Resolution via Cascaded Transformers Guidance
I Ariav, I Cohen - Frontiers in Signal Processing, 2022 - frontiersin.org
Depth information captured by affordable depth sensors is characterized by low spatial
resolution, which limits potential applications. Several methods have recently been …
resolution, which limits potential applications. Several methods have recently been …
Improved Upsampling Based Depth Image Super-Resolution Reconstruction
Y Ye, M Zhou, Z Wang, X Shen - IEEE Access, 2023 - ieeexplore.ieee.org
Constrained by current sensing technology, depth camera only acquires a low-resolution
depth image that does not meet actual requirements. To solve this problem, this paper take a …
depth image that does not meet actual requirements. To solve this problem, this paper take a …